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Sequential Modular Simulation of Hydrodynamics and Reaction Kinetics in a Biomass Bubbling Fluidized Bed Gasifier using Aspen Plus Mohammad Rafati, Abolhasan Hashemisohi, Lijun Wang, and Abolghasem Shahbazi Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.5b02097 • Publication Date (Web): 18 Nov 2015 Downloaded from http://pubs.acs.org on November 19, 2015
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Sequential Modular Simulation of Hydrodynamics and Reaction Kinetics in a Biomass Bubbling Fluidized Bed Gasifier using Aspen Plus Mohammad Rafati a, Abolhasan Hashemisohi b, Lijun Wang c, d *, Abolghasem Shahbazi c, d a
Department of Energy and Environmental Systems, North Carolina A&T State University,
Greensboro, North Carolina 27411, USA. b
Department of Computational Science and Engineering, North Carolina A&T State University,
Greensboro, North Carolina 27411, USA. c
Department of Natural Resources and Environmental Design, North Carolina A&T State
University, Greensboro, North Carolina 27411, USA. d
Department of Chemical, Biological, and Bioengineering, North Carolina A&T State
University, Greensboro, North Carolina 27411, USA. *
Corresponding author:
[email protected], Tel: (+1) 336-285-3833
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Abstract A sequential modular simulation (SMS) approach was used to simulate hydrodynamics and detailed kinetics of a fluidized bed biomass gasifier in Aspen Plus. The kinetics of tar cracking reactions was taken into account in the simulation. The effects of operating conditions including temperature, equivalence ratio (ER), and steam to biomass ratio (SBR) on the composition and the lower heating value (LHV) of the effluent gas were studied and compared with experimental data. The model predictions well agreed with the experimental data. The increase of the bed temperature significantly decreased the tar content and increased the hydrogen content of the product gas. At ER value of 0.3, the increase of the temperature from 973 K to 1123 K resulted in the increase of H2 molar concentration in the product gas from 7.6% to 11.3% and CO molar concentration from 13.1% to 17.0%. At temperature of 1073 K, the optimum ER was 0.3 and the increase of ER from 0.2 to up to 0.3 increased the amount of fuel gases but the further increase of ER shifted the system kinetics toward the combustion regime. At 1073 K and ER of 0.3, with an increase in SBR from 0 to 1.0, H2 and CO2 concentrations increased from 9.3% and 13.3% to 10.8% and 14.7%, respectively and CO concentration decreased from 15.8% to 12.9%. The analysis showed the SMS model with 4 stages gives the most satisfactory predictions by comparing with the experimental data.
1. Introduction Biomass and coal can be gasified into a mixture of dominantly H2, CO and CO2, called syngas for further clean power generation and liquid fuel synthesis
1-4
. The operating conditions of the
gasifier such as temperature and flow rate of the gasifying agent can be optimized for the specific downstream application of syngas. 2 ACS Paragon Plus Environment
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Biomass gasification reactors are categorized into four major types of fixed bed, moving bed, fluidized bed and entrained flow. Fixed bed and moving bed gasifiers produce a large amount of tar and char due to the inefficient heat and mass transfer between the solid and the gas phases 5. The entrained flow gasifiers are operated at higher temperatures which would help to reduce the tar content of the product gas but the high grinding costs and low energy density of the biomass feedstock offset such advantage 6. The fluidized bed gasifiers, on the other hand, take the advantage of vigorous mixing characteristics and high reaction rates of gas-solid phases. In addition, a catalytic material such as dolomite and spent FCC catalyst can be easily added to the bed medium to improve the tar cracking properties 7. Several studies have been published for better understanding the operational parameters that affect the performance of a bubbling fluidized bed gasifier (BFBG) system using computer simulation
8-12
. The BFBG system involves complicated hydrodynamics, heat and mass transfer
and reaction kinetics. The computational fluid dynamics (CFD) is the most accurate simulation tool to analyze complicated physical and chemical phenomena in a BFBG but it is intensively time and resource consuming13-15. Some research groups have used an empirical two phase model to simulate the hydrodynamics in a BFBG system8, 10, 16, 17. When truly implemented, this approach would result in satisfactory model predictions with respect to experimental data. The commercial process modeling package of Aspen Plus is widely used to simulate large chemical processes. Commercial process simulators conveniently contain built-in models for a variety of unit operations and equipment, and can be used to calculate mass and energy balances across all the unit operations in a plant. Although those packages contain a variety of standard reactor models such as plug flow reactors (PFR), continuous stirring tank reactors (CSTR) and equilibrium reactors, they do not contain an intrinsic reactor model that can be used to simulate 3 ACS Paragon Plus Environment
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both hydrodynamics and reaction kinetics in a BFBG system. In the literature, two approaches have been taken to simulate a BFBG using Aspen Plus: complete (or restricted) equilibrium models and semi-detailed kinetic models. The equilibrium-based models fail to predict the gasifier behavior over a range of operating conditions e.g. various operating temperatures and equivalence ratios (ER)
18-22
. In these models, an appropriate temperature approach typically
needs to be found and set so that the model predictions would match with the experimental data. This would limit the interactive use of such models for the study and optimization of a gasifier. As can be seen in the Figure 1, equilibrium calculations strongly overpredict H2 and CO concentrations while underpredicting H2O and CO2 concentrations with literally no CH4 and tar at the gasifier exit. Generally, thermodynamic equilibrium does not favor the presence of most of hydrocarbons at typical gasifier operating temperatures. Some Aspen Plus-based models used one or two continuous stirred tank reactors (CSTR) to simulate the hydrodynamics of a BFBG reactor 12, 23. Since a fluidized bed reactor is not a traditional reactor like a CSTR and plug flow reactor (PFR), it could not be well predicted using either a CSTR or PFR that are available kinetic reactor modules in Aspen Plus. Recently, a sequential modular simulation (SMS) approach has been developed to simulate a fluidized bed reactor 24-27. In this method, a fluidized bed reactor was divided into several stages of CSTR and PFR pairs. At each stage, the CSTR and the PFR represent the emulsion and bubble phases, respectively. Mass and heat transfer occurs between the bubble and emulsion phases at the end of each stage. Following this strategy, fluidized beds have been implemented in Aspen Plus for a number of process setups (e.g. Porrazzo et al. the chemical looping combustion; Sarvar-Amini et al.
28
24
modelled a fluidized bed for
modelled a fluidised bed membrane
reactor; Bashiri et al. 29 modeled a fluidised bed reformer; and Sotudeh-Gharebaagh et al. 30 and 4 ACS Paragon Plus Environment
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Liu et al.
31
modelled a fluidised bed for coal combustion). In this paper, a BFBG system was
modeled using the SMS approach in the Aspen Plus for the first time. The developed model also took into account of detailed kinetics of tar decomposition which was not considered in many previous well-known models
32-36
. These reactions have a profound effect on the quality of the
syngas produced by biomass gasification compared to the coal gasification. A set of experimental data
37, 38
was used to evaluate the model predictions at various operating
conditions including operating temperature and equivalence ratio. This model can be integrated as a sub-model into larger Aspen Plus process models such as biofuel production through further methanol synthesis, Fischer-Tropsch synthesis, and H2 production, and improve the systematic study and optimization of such processes.
2. System description and modeling approach A schematic of a typical BFBG system is presented in Figure 2. Air and steam pass through a distributor to ensure the uniform velocity and temperature profiles at the bottom of the reactor. The biomass feeder is located just above the distributor. The biomass gasification reactor has two regions: dense bed at the bottom and freeboard at the top. The dense bed of a fluidized bed gasifier consists of two phases, the emulsion phase with vigorously mixed gas and solid particles (biomass and bed material), and the bubble phase with a dominant amount of gas and a negligible amount of solid particles. The freeboard should be long enough on top of the bed to prevent the solid entrainment and maintain the proper residence time of gas volatiles for the homogenous reactions among the volatiles such as the tar cracking reactions. The SMS approach was used to model a fluidized bed gasifier. In this approach, the dense bed region was axially divided into a series of CSTRs and PFRs in several stages, as shown in Figure 3. At each stage,
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the CSTR and the PFR represent the emulsion and bubble phases, respectively. Mass transfer occurs between the bubble and emulsion phases at the end of each stage. The freeboard was considered as a plug flow reactor due to the absence of solid particles and the piston-type movement of the gas in this region.
2.1 Model Validation Experimental data reported in literature that was collected on a fluidized bed reactor with the same design and operating parameters as shown in Figure 2 were used to validate the predictions of the model 39. The biomass of pine wood sawdust (Table 1) was fed at the bottom of the bed just above the distributor plate. The particles sizes were between 400 µm and 800 µm. The silica sand particles in the size range of 320 µm to 500 µm were used in the bed to maintain the temperature and enhance the mixing. Air was used as the gasifying agent and fluidizing gas.
2.2 Hydrodynamic Sub-Model The bubbling and turbulent fluidization regime is formed at the gas velocities higher than the minimum fluidization and less than the terminal velocity of particles in the reactor. The bubble formation starts suddenly after passing the minimum fluidization velocity for the particles categorized under the Geldart B category
40
. The bubbling gasifier works at the superficial
velocities (U0) around 2-3 times of the minimum fluidization velocity (Umf). A dynamic twophase structure model
41
was employed to model the bubbling bed for which the required
hydrodynamic parameters are given in Table 2. The temperatures of bed and freeboard regions were considered to be constant according to experimental data given in the reference bubble diameter was assumed to be constant within the bed
41
39
. The
, and the change in the sand
diameter due to the erosion was neglected. 6 ACS Paragon Plus Environment
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The molar balance of specie A in the bubble phase can be written as follows:
, − , − , −, , − , = 0
(Eq. 1)
Similarly, the molar balance of the specie A in the emulsion phase can be written as: , − , "#$%, + , − , , '
(
(
) − , = 0
(Eq. 2)
The diffusivities of gas components are needed to calculate the mass transfer coefficients (Kbe) in Table 2. The diffusivity of each component in N2 was used to represents its diffusivity in the gas mixture inside the gasifier, as N2 is the most abundant component in an air-blown gasifier accounting for 50-60 vol% of the total gas in various operating conditions. The binary diffusivities are calculated using the Fuller-Schettler-Giddings correlation
42
and listed in Table
3.
2.3 Kinetic Sub-Model The major reactions and processes occurring inside a gasifier can be categorized into four groups: 1) Drying: this step takes place quickly at the feeding region in which the moisture content is released by evaporation. 2) Devolatilization (primary pyrolysis): In this step, the major fraction of biomass is flashed into a mixture of volatiles and char at a high temperature in the absence of oxygen. The volatiles of the devolatilization reaction consist of mainly CO, CO2, H2, oxygenates, light hydrocarbons, water, and tar compounds. It was assumed that devolatilization reactions take
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place instantaneously at the feeding zone of a BFBG
10, 43, 44
biomass devolatilization was taken from the literature
45
. The product distribution of
and listed in Table 4. The mass
yields of devolatilization products at 973 K were used in the model. Carbon is assumed to be the only constituent of the char. The tar is comprised of more than hundred compounds and its actual composition greatly depends on the temperature at the devolatilization zone of the gasifier. For the sake of simplification and reducing the number of components in the model, phenol was chosen as the tar model compound, as discussed by Gerun et al 14. 3) Homogenous reactions: gaseous compounds generated in the devolatilization step undergo various chemical reactions as they ascend inside the gasifier. All other homogenous reactions except CO oxidation also takes place in the emulsion phase. CO oxidation reaction is strongly prohibited in the emulsion phase due to the presence of the sand particles 46. Tar and other gases from the biomass devolatilization participate in several reactions which are listed in Table 5. Benzene and naphthalene are assumed to be the product of the decomposition of phenol which will undergo further reactions such as decomposition and combustion. The partial combustion of devolatilization gases including methane and tars occurs in the gasifier with a low oxygen concentration (mass of air to fuel at ~1 to 4), so a two-step reaction approach was considered
47
. The first step converts the hydrocarbons to CO and H2O (r2-r6). The CO is
then oxidized to CO2 by the reaction (r1). The hydrogen oxidation (r12) and the water-gas shift (WGS, r13) are other important reactions which could strongly influence the final syngas composition. The widely used rate expression for the WGS reaction in the literature 48 was very fast, which caused almost 100% conversion of CO at typical gasification temperatures. In this work, a modified expression recently proposed by Stark et al.
9
was used, as listed in Table 5
(reaction r13). 8 ACS Paragon Plus Environment
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4) Heterogeneous reactions: char produced in the biomass devolatilization is considered to undergo three reactions, listed in Table 6. The char produced from the devolatilization accounts for 5 to 20 wt% of total carbon in the biomass
9, 45
, depending on the condition of
the devolatilization. In our simulation conditions, this value was assumed to be 6% which resulted in carbon conversion of up to 98 wt% in the gasifier. Char combustion is the fastest reaction among all heterogeneous reactions for which the rate depends on the instantaneous surface area of char particle. In the equation (r14) in Table 4, the term (1 − +" )., accounts for the change in the surface area of char during the reaction. Moreover, to use the surface reaction rate of r15 in Aspen Plus, it was converted into volumetric form (kmol/m3reactor.s) taking into account the core shrinking model as follows 24: . = -
/(0)(12 )3/5
(Eq. 3)
67 0
where , Xc, and dp are the reactor voidage, instantaneous char (carbon) conversion, and initial char particle diameter, respectively.
2.4 Implementation of the Model in Aspen Plus The RK-Aspen (Redlich−Kwong−Aspen) equation of state was chosen for the calculation of thermodynamic properties of chemical compounds in Aspen Plus, which was widely used for the simulation of hydrocarbon processing applications, such as gas-processing, refinery, and petrochemical processes 49. The stream type of the flowsheet was set as “MIXCINC” which considers both conventional and nonconventional solids without the particle size distribution. Biomass particles are assumed to be spherical and of uniform size. The biomass particle diameter was assumed to be 600 um, which was the average particle size reported in the reference 39. 9 ACS Paragon Plus Environment
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Since the volume ratio of the biomass to sand was very low in the bed, the sand would dominantly affect the hydrodynamics in the bed. In this case, the shape and size of the biomass particles would not significantly affect the hydrodynamics of the bed. Previous studies showed that in the range of particle sizes of this study, the internal heat transfer limitation is negligible 50. Moreover, the yield of the different products in pyrolysis of biomass in fluidized bed has been shown to be independent of the particle size in the range of 4 µm to 2 mm 17, 51. Several reactor blocks were employed to properly simulate a BFBG reactor in Aspen Plus, as depicted in Figure 3. Table 7 also gives a brief description of each unit operation block. The flowsheet begins with the biomass feedstock (stream BMASS) which was defined using the proximate and ultimate analysis data listed in Table 1. The biomass was then fed to the gasifier by sending it to the DEVOL block, representing the devolatilization step. It was assumed that drying of the biomass takes places place in this block as well. The yields of devolatilization products were set according to the data in Table 4. The devolatilization products are combined with the air (or/and steam) and then directed through the bed. An MS Excel calculator (SPLT) was used to calculate the volumetric flow rates of bubbling and emulsion phases as well as the volumes of CSTRs and PFRs at each stage, based on hydrodynamic parameters in Tables 2 and 8. The gas mixture is directed into the series of CSTR and PFR sub-reactors representing the gas flow through the emulsion and bubbles phases, respectively. The number of stages (CSTR/PFR pairs) was varied between 2 to 5 to find the optimum configuration which results in satisfactory predictions. Two separate FORTRAN subroutines were written to nest the reaction kinetics data (Tables 5 and 6) into the CSTRs and PFRs. All heterogeneous and homogenous reactions except the CO oxidation reaction (r1) were considered to take place in CSTRs while only homogenous 10 ACS Paragon Plus Environment
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gas phase reactions took place in PFRs. The data required to implement the heterogeneous reaction rates (reactions r13-r16) including the char concentration at the CSTR inlet as well as the residence time and the char volume were passed to the kinetics subroutine using the calculator blocks in Aspen Plus. The Wegstein method
52
was used as the convergence solver for
calculating the mass balance on the streams from and to the sub-reactors in each stage. After each stage, mass transfer between the bubble and emulsion phases occurs at outlet streams of each stage, before entering the next stage, as shown in Figure 3. Considering the mass transfer between the emulsion and bubble phases, the concentration of each specie at the beginning of the next stage is defined as: , = , − , −,
9:,
, = , + , −,
9:,
(Eq. 4)
;
(
'()
(Eq. 5)
A different expression was used if the calculated concentration at ith stage from Eq. 4 and Eq. 5 becomes negative or if the mass driving force principle was not satisfied 24:
@
(Eq. 6)
@
(Eq. 7)
, = , ', + , @> )
